EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone.

Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android)...

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Publicado en:BioMed Research International Vol. 2017; pp. 1 - 13
Autores principales: Blum, Sarah, Debener, Stefan, Emkes, Reiner, Volkening, Nils, Fudickar, Sebastian, Bleichner, Martin G.
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell 11/16/2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 11/16/2017
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      pub: Wiley-Blackwell
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        10.1155/2017/3072870
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        atl: EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone.
      aug:
        au:
          Blum, Sarah
          Debener, Stefan
          Emkes, Reiner
          Volkening, Nils
          Fudickar, Sebastian
          Bleichner, Martin G.
        affil: Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
      sug:
        subj:
          Electrocardiography Methods
          Online Services
          Smartphone
          Mobile Applications
          Human
          Brain Physiology
          Brain-Computer Interfaces
          Signal Processing, Computer Assisted
          Software Design
          Communication
          Computer Hardware
          Data Collection
          Auditory Perception
          Sound
          Technology
      ab: Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.
      pubtype: Academic Journal
      doctype:
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      ougenre: Article
    language: English
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